Media overlay selection system

ABSTRACT

A computing system receives, from a client device, image data describing an image captured by an optical sensor of the client device. The computing system compares the image to a set of reference images that include associated metadata describing a real-world feature depicted by the respective reference image. The computing system determines, based on the comparison, a subset of reference images that are similar to the image, and then determines, based on associated metadata of the subset of reference images, that the image captured by the optical sensor of the client device depicts a first real-world feature. The computing system selects a subset of media overlays related to the first real-world feature based on metadata associated with each media overlay that describes the respective media overlay. The computing system transmits the subset of media overlays to the client device.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of and claims the benefit ofpriority to U.S. patent application Ser. No. 16/653,561, filed Oct. 15,2019, which application is a continuation of and claims the benefit ofpriority to U.S. patent application Ser. No. 15/801,853, filed on Nov.2, 2017, which claims the benefit of priority of U.S. ProvisionalApplication No. 62/447,693, filed on Jan. 18, 2017, U.S. Pat. No.10,482,327, which are incorporated herein by reference in theirentirety.

TECHNICAL FIELD

Embodiments of the present disclosure relate generally to selectingmedia overlays. More particularly, but not by way of limitation,embodiments of the present disclosure relate to selecting a filtered setof media overlays based on real-world features identified in an image.

BACKGROUND

Current applications allow users to capture and alter images. Forexample, some applications provide users with a set of features that theuser can use to alter the captured image by adjusting colors, applyingfilters, overlaying additional content on the image, etc. Whileproviding a large set of features can be beneficial to a user, it canalso be costly with regard to resource usage and cause overall systemlatency. For example, a large set of content that may be overlaid overan image uses considerable memory. This becomes particularly problematicwhen using mobile computing devices that generally include limitedmemory to store data. Providing large data sets is also problematic tothe end user that may become overwhelmed with the large data set,finding it hard to find relevant content for use with a captured image.Accordingly, improvements are needed.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

To easily identify the discussion of any particular element or act, themost significant digit or digits in a reference number refer to thefigure number in which that element is first introduced.

FIG. 1 is a block diagram showing an example messaging system toexchange data (e.g., messages and associated content) over a network.

FIG. 2 is block diagram illustrating further details regarding amessaging system, according to example embodiments.

FIG. 3 is a schematic diagram illustrating data which may be stored inthe database of the messaging server system, according to certainexample embodiments.

FIG. 4 is a schematic diagram illustrating a structure of a message,according to some embodiments, generated by a messaging clientapplication for communication.

FIG. 5 is a schematic diagram illustrating an example access-limitingprocess, in terms of which access to content (e.g., an ephemeralmessage, and associated multimedia payload of data) or a contentcollection (e.g., an ephemeral message story) may be time-limited (e.g.,made ephemeral).

FIG. 6 is a block diagram illustrating various modules of the image:processing system, according to certain example embodiments.

FIG. 7 is a block diagram illustrating various modules of an annotationsystem, according to certain example embodiments.

FIG. 8 is a flowchart illustrating a method to select a filtered set ofmedia overlays based on real-world features identified in an image,according to certain example embodiments.

FIG. 9 is a flowchart illustrating another method to select a filteredset of media overlays based on real-world features identified in animage, according to certain example embodiments.

FIG. 10 is a flowchart illustrating a method to determine a subset ofreference images that are similar to a target image, according tocertain example embodiments.

FIG. 11 is a flowchart illustrating a method to determine the real-worldfeature captured in an image, according to certain example embodiments.

FIG. 12 is a flowchart illustrating a method to select a media overlay,according to certain example embodiments.

FIG. 13 is a flowchart illustrating another method to select a mediaoverlay, according to certain example embodiments.

FIG. 14 is a block diagram illustrating a representative softwarearchitecture, which may be used in conjunction with various hardwarearchitectures herein described.

FIG. 15 is a block diagram illustrating components of a machine,according to some example embodiments, able to read instructions from amachine-readable medium (e.g., a machine-readable storage medium) andperform any one or more of the methodologies discussed herein.

DETAILED DESCRIPTION

The description that follows includes systems, methods, techniques,instruction sequences, and computing machine program products thatembody illustrative embodiments of the disclosure. In the followingdescription, for the purposes of explanation, numerous specific detailsare set forth in order to provide an understanding of variousembodiments of the inventive subject matter. It will be evident,however, to those skilled in the art, that embodiments of the inventivesubject matter may be practiced without these specific details. Ingeneral, well-known instruction instances, protocols, structures, andtechniques are not necessarily shown in detail.

Drawings

FIG. 1 is a block diagram showing an example messaging system 100 toexchange data (e.g., messages and associated content) over a network.The messaging system 100 includes multiple client devices 102, each ofwhich hosts a number of applications, including a messaging clientapplication 104. Each messaging client application 104 iscommunicatively coupled to other instances of the messaging clientapplication 104 and a messaging server system 108 via a network 106(e.g., the Internet).

Accordingly, each messaging client application 104 can communicate andexchange data with another messaging client application 104 and with themessaging server system 108 via the network 106. The data exchangedbetween messaging client applications 104, and between a messagingclient application 104 and the messaging server system 108, includesfunctions (e.g., commands to invoke functions) as well as payload data(e.g., text, audio, video or other multimedia data).

The messaging server system 108 provides server-side functionality viathe network 106 to a particular messaging client application 104. Whilecertain functions of the messaging system 100 are described herein asbeing performed by either a messaging client application 104 or by themessaging server system 108, it will be appreciated that the location ofcertain functionality either within the messaging client application 104or the messaging server system 108 is a design choice. For example, itmay be technically preferable to initially deploy certain technology andfunctionality within the messaging server system 108, but to latermigrate this technology and functionality to the messaging clientapplication 104 where a client device 102 has a sufficient processingcapacity.

The messaging server system 108 supports various services and operationsthat are provided to the messaging client application 104. Suchoperations include transmitting data to, receiving data from, andprocessing data generated by, the messaging client application 104. Thisdata may include message content, client device information, geolocationinformation, media annotation and overlays, message content persistenceconditions, social network information, and live event information, asexamples. Data exchanges within the messaging system 100 are invoked andcontrolled through functions available via user interfaces (UIs) of themessaging client application 104.

Turning now specifically to the messaging server system 108, anApplication Program Interface (API) server 110 is coupled to, andprovides a programmatic interface to, an application server 112. Theapplication server 112 is communicatively coupled to a database server118, which facilitates access to a database 120 in which is stored dataassociated with messages processed by the application server 112.

Dealing specifically with the API server 110, this server receives andtransmits message data (e.g., commands and message payloads) between theclient device 102 and the application server 112. Specifically, the APIserver 110 provides a set of interfaces (e.g., routines and protocols)that can be called or queried by the messaging client application 104 inorder to invoke functionality of the application server 112. The APIserver 110 exposes various functions supported by the application server112, including account registration; login functionality; the sending ofmessages, via the application server 112, from a particular messagingclient application 104 to another messaging client application 104, thesending of media files (e.g., images or video) from a messaging clientapplication 104 to the messaging server application 114; and, forpossible access by another messaging client application 104, the settingof a collection of media data (e.g., story); the retrieval of a list offriends of a user of a client device 102; the retrieval of suchcollections; the retrieval of messages and content; the adding anddeletion of friends to a social graph; the location of friends within asocial graph; and opening an application event (e.g., relating to themessaging client application 104).

The application server 112 hosts a number of applications andsubsystems, including a messaging server application 114, an imageprocessing system 116, and a social network system 122. The messagingserver application 114 implements a number of message processingtechnologies and functions, particularly related to the aggregation andother processing of content (e.g., textual and multimedia content)included in messages received from multiple instances of the messagingclient application 104. As will be described in further detail, the textand media content from multiple sources may be aggregated intocollections of content (e.g., called stories or galleries). Thesecollections are then made available, by the messaging server application114, to the messaging client application 104. Other processor and memoryintensive processing of data may also be performed server-side by themessaging server application 114, in view of the hardware requirementsfor such processing.

The application server 112 also includes an image processing system 116that is dedicated to performing various image processing operations,typically with respect to images or video received within the payload ofa message at the messaging server application 114. For example, theimage processing system 116 uses image processing operations to identifyone or more real-world features captured in an image. A real-worldfeature is any type of item or feature captured in an image. Examples ofreal-world features include physical objects, such as people, bottles,automobiles, storefronts, signs, etc. Additional examples of real-worldfeatures include features that describe a context of the image, such asthe weather (e.g., sunny, rainy etc.) or time of year (e.g., fall,spring, etc.).

The image processing system 116 uses a set of reference images toidentify real-world features in an image. The set of reference images isstored in the database 120. Each reference image is associated withmetadata describing a real-world feature captured by the referenceimage. The metadata includes metadata indicating what the real-worldfeature is, as well as categorization data describing one or morecategories with which the real-world feature is associated. For example,a reference image of a shoe is associated with metadata indicating thatthe reference image is of a shoe, as well as categorization datadescribing categories associated with the shoe, such as apparel,footwear, sporting goods, basketball, running, Nike, Adidas, etc. Asanother example, a reference image of a guitar is associated withmetadata indicating that the reference image is of a guitar, as well ascategorization data describing categories associated with the guitarsuch as music, musical instrument, acoustic, electric, rock, jazz,Fender, Gibson, etc.

The image processing system 116 operatively compares an image to thereference images in the database 120 to identify real-world features inthe image. For example, the image processing system 116 compares animage to one or more reference images to identify reference images thatare similar to the image. The image processing system 116 generatesvectors representing the images and uses distance functions to identifyvectors that are close to each other, indicating that theircorresponding images are the same or similar. Each vector includes a setof numeric values that represent elements of the image. For example, thenumerical values may represent an intensity value of each pixel of theimage. Other examples of elements include color components, length,area, circularity, gradient magnitude, gradient direction, thegray-level intensity value, etc.

The image processing system 116 generates a target vector based on animage received from a client device 102 and compares the target vectorto a set of reference vectors representing the reference images. Thereference images and the reference vectors are stored in the database120. The image processing system 116 uses any known distance function todetermine the distance between the target vector and the referencevectors. The image processing system 116 identifies the referencevectors that are closest and/or within a threshold distance of thetarget vector. The reference images represented by the identifiedreference vectors are determined to be similar to the target image.

Once the image processing system 116 has identified one or morereference images that are similar to the image, the image processingsystem 116 uses metadata associated with the identified reference imagesto determine real-world features included in the image. For example, areference image associated with metadata indicating that the referenceimage is of a guitar is used to determine that the image is also of aguitar. Additionally, categorization data associated with the referenceimage is used to categorize the image.

In some instances, a reference image determined by the image processingsystem 116 to be similar to the image may in fact be of a real-worldfeature that is different than the real-world feature captured in theimage. To avoid incorrectly identifying real-world features in an image,the image processing system 116 determines whether a threshold number orthreshold percentage of similar reference images provide consistentmetadata to determine the real-world feature included in the image. Forexample, to determine that an image is of a shoe, the image processingsystem 116 determines whether at least three reference images determinedto be similar to the image include metadata indicating that thereference image is of a shoe. As a result, a single incorrectlyidentified reference image will not cause the image processing system116 to incorrectly identify the real-world feature in the image.

As another example, the image processing system 116 determines whether athreshold percentage of the identified reference images includeconsistent metadata describing the real-world feature in the referenceimage. For example, the image processing system 116 determines whetherat least 50% of the reference images identified as being similar to theimage include consistent metadata to cause the image processing system116 to determine that the image includes the same real-world feature.Thus, if the image processing system 116 identifies ten reference imagesas being similar to an image, and at least five of the ten referenceimages are identified as being of a guitar, the image processing system116 determines that the image also is of a guitar.

In some embodiments, the image processing system 116 compares an entireimage to reference images to determine real-world features included inthe image. Alternatively, the image processing system 116 compares aportion of the image to the reference images to determine real-worldfeatures included in the portion of the image. For example, the imageprocessing system 116 divides an image into portions and compares eachindividual portion to the reference images. In some embodiments, theimage processing system 116 divides the image in a predetermined manner,such as dividing the image into equal halves, quarters, etc.

In some embodiments, the image: processing system 116 divides an imagebased on potential real-world features determined to be captured in theimage. For example, the image processing system 116 analyzes an imagefor changes in color or shading to identify boundaries of potentialreal-world features included in the image. The image processing system116 then extracts a portion of the image based on the identifiedboundaries and compares the extracted portion to the reference images todetermine the real-world feature captured in the extracted portion ofthe image.

Although use of reference images is described as being used by the imageprocessing system 116 to determine real-world features included in animage, this is just one example and not meant to be limiting. The imageprocessing system 116 can use any known technique to analyze images andidentify real-world features in the image, and this disclosure envisionsuse of any such techniques.

Once the image processing system 116 has identified one or morereal-world features in an image, the messaging server system 108 selectsand provides a user with media overlays for use with the image based onone or more of the real-world features. For example, the messagingserver system 108 selects one or more media overlays based on theidentified real-world features and provides the selected media overlaysto a client device 102 of the user. Selecting media overlays based onthe real-world features included in an image is described in greaterdetail below.

The social network system 122 supports various social networkingfunctions and services, and makes these functions and services availableto the messaging server application 114. To this end, the social networksystem 122 maintains and accesses an entity graph within the database120. Examples of functions and services supported by the social networksystem 122 include the identification of other users of the messagingsystem 100 with which a particular user has relationships or is“following,” and also the identification of other entities and interestsof a particular user.

The application server 112 is communicatively coupled to a databaseserver 118, which facilitates access to a database 120 in which isstored data associated with messages processed by the messaging serverapplication 114.

FIG. 2 is block diagram illustrating further details regarding themessaging system 100, according to example embodiments. Specifically,the messaging system 100 is shown to comprise the messaging clientapplication 104 and the application server 112, which in turn embody anumber of subsystems, namely an ephemeral timer system 202, a collectionmanagement system 204, and an annotation system 206.

The ephemeral timer system 202 is responsible for enforcing thetemporary access to content permitted by the messaging clientapplication 104 and the messaging server application 114. To this end,the ephemeral timer system 202 incorporates a number of timers that,based on duration and display parameters associated with a message, orcollection of messages (e.g., a SNAPCHAT story), selectively display andenable access to messages and associated content via the messagingclient application 104. Further details regarding the operation of theephemeral timer system 202 are provided below.

The collection management system 204 is responsible for managingcollections of media (e.g., collections of text, image, video, and audiodata). In some examples, a collection of content (e.g., messages,including images, video, text, and audio) may be organized into an“event gallery” or an “event story.” Such a collection may be madeavailable for a specified time period, such as the duration of an eventto which the content relates. For example, content relating to a musicconcert may be made available as a “story” for the duration of thatmusic concert. The collection management system 204 may also beresponsible for publishing an icon that provides notification of theexistence of a particular collection to the user interface of themessaging client application 104.

The collection management system 204 furthermore includes a curationinterface 208 that allows a collection manager to manage and curate aparticular collection of content. For example, the curation interface208 enables an event organizer to curate a collection of contentrelating to a specific event (e.g., delete inappropriate content orredundant messages). Additionally, the collection management system 204employs machine vision (or image recognition technology) and contentrules to automatically curate a content collection. In certainembodiments, compensation may be paid to a user for inclusion of usergenerated content into a collection. In such cases, the curationinterface 208 operates to automatically make payments to such users forthe use of their content.

The annotation system 206 provides various functions that enable a userto annotate or otherwise modify or edit media content associated with amessage:. For example, the annotation system 206 provides functionsrelated to the generation and publishing of media overlays for messagesprocessed by the messaging system 100. The annotation system 206operatively supplies a media overlay (e.g., a SNAPCHAT filter, digitalsticker, etc.) to the messaging client application 104 based on ageolocation of the client device 102. In another example, the annotationsystem 206 operatively supplies a media overlay to the messaging clientapplication 104 based on other information, such as social networkinformation of the user of the client device 102, sensor data receivedfrom the client device 102. real-world features identified in an imagecaptured by an optical sensor of the client device 102, etc. A mediaoverlay may include audio and visual content and visual effects.Examples of audio and visual content include pictures, texts, logos,animations, and sound effects. An example of a visual effect includescolor overlaying. The audio and visual content or the visual effects canbe applied to a media content item (e.g., a photo) at the client device102. For example, the media overlay includes text that can be overlaidon top of an image (e.g., photograph) captured by the client device 102.In another example, the media overlay includes an identification of alocation overlay (e.g., Venice beach), a name of a live event, or a nameof a merchant overlay (e.g., Beach Coffee House). In another example,the annotation system 206 uses the geolocation of the client device 102to identify a media overlay that includes the name of a merchant at thegeolocation of the client device 102. The media overlay may includeother indicia associated with the merchant. The media overlays may bestored in the database 120 and accessed through the database server 118.

In some embodiments, the annotation system 206 uses real-world featuresidentified in an image to identify media overlays to provide to a user.For example, a real-world feature identified in an image can be aphysical object such as a guitar, automobile, snowboard, etc., and theannotation system 206 identifies media overlays based on the identifiedphysical object. instance, the annotation system 206 identifies mediaoverlays that depict the identified physical object in the image. Thus,in response to determining that an image includes a real-world featurethat is a guitar, the annotation system 206 identifies media overlaysdepicting guitars. As another example, the annotation system 206identifies media overlays that depict shoes for an image determined toinclude a real-world feature that is a shoe. Utilizing real-worldfeatures captured in the image to select a subset of targeted mediaoverlays to provide to a user reduces resource usage. For example,rather than providing the user with the entire set of media overlays,which would use considerable resources to transmit and store, theannotation system 206 provides the user with a subset of targeted mediaoverlays that is smaller than the entire set. The resources used tostore and transmit the subset of targeted media overlays is less thanwhat would have been used to store and transmit the entire set.

In some embodiments, the annotation system 206 identifies media overlaysthat depict images that are related to real-world features included inthe image. The annotation system 206 uses categorization data associatedwith a real-world feature to identify media overlays that are within thesame or similar category. For example, a real-world feature such as aguitar is generally categorized under music, and the annotation system206 selects a media overlay that is also categorized under music, suchas a media overlay depicting an image of a musical note, plano, drumset, rock band, etc. As another example, a real-world feature such as abasketball is generally categorized under sports, and the annotationsystem 206 selects media overlays that are also categorized undersports, such as media overlays depicting a football, scoreboard,stadium, foam finger, etc. The media overlays may be stored in thedatabase 120 and accessed through the database server 118.

In one example embodiment, the annotation system 206 provides auser-based publication platform that enables users to select ageolocation on a map and upload content associated with the selectedgeolocation. The user may also specify circumstances under which aparticular media overlay should be offered to other users. Theannotation system 206 generates a media overlay that includes theuploaded content and associates the uploaded content with the selectedgeolocation.

In another example embodiment, the annotation system 206 provides amerchant-based publication platform that enables merchants to select aparticular media overlay associated with a geolocation, a real-worldfeature, etc., via a bidding process. For example, the annotation system206 associates the media overlay of a highest bidding merchant with acorresponding geolocation, real-world feature, determined image context,etc., for a predefined amount of time.

FIG. 3 is a schematic diagram 300 illustrating data which may be storedin the database 120 of the messaging server system 108, according tocertain example embodiments. While the content of the database 120 isshown to comprise a number of tables, it will be appreciated that thedata could be stored in other types of data structures (e.g., as anobject-oriented database).

The database 120 includes message data stored within a message table314. The entity table 302 stores entity data, including an entity graph304. Entities for which records are maintained within the entity table302 may include individuals, corporate entities, organizations, objects,places, events etc. Regardless of type, any entity regarding which themessaging server system 108 stores data may be a recognized entity. Eachentity is provided with a unique identifier, as well as an entity typeidentifier (not shown).

The entity graph 304 furthermore stores information regardingrelationships and associations between entities. Such relationships maybe social, professional (e.g., work at a common corporation ororganization), interested-based, or activity-based.

The database 120 also stores annotation data, in the example form offilters and media overlays, in an annotation table 312. Filters andmedia overlays, for which data is stored within the annotation table312, are associated with and applied to videos (for which data is storedin a video table 310) and/or images (for which data is stored in animage table 308). In one example, an image overlay can be displayed asoverlaid on an image or video during presentation to a recipient user.For example a user may append a media overlay on a selected portion ofthe image, resulting in presentation of an annotated image that includesthe media overlay over the selected portion of the image. In this way, amedia overlay is used as a digital sticker that a user uses to annotateor otherwise enhance the images they capture (e.g., photographs).

Each stored media overlay is associated with metadata describing themedia overlay. For example, the media overlay is associated withmetadata describing a physical item or action depicted by the mediaoverlay, such as a guitar, shoes, running. etc. The metadata alsoincludes categorization data describing one or more categoriesassociated with the media overlay. For example, a media overlaydepicting an image of a guitar is associated with categories such asmusic, rock and roll, musical instruments, etc. In some embodiments, thecategorization data includes various levels of categories associatedwith a media overlay. For example, the categorization data identifies ageneral categorization for a media overlay that describes the mediaoverlay at a high level, as well as one or more specific categorizationlevels that describe the media overlay with greater specificity. Forexample, a media overlay depicting a guitar is assigned a generalcategorization of music, and more specific categorizations such asmusical instruments, guitars, electric guitars, etc. The categorizationdata also includes a contextual categorization of a media overlay thatdescribes a context with which the media overlay is associated. Forexample, a contextual categorization such as a sunny day includes mediaoverlays depicting images such as beach balls, hot dogs, baseball, etc.

Filters may be of various types, including user-selected filters from agallery of filters presented to a sending user by the messaging clientapplication 104 when the sending user is composing a message. Othertypes of filters include geolocation filters (also known as geo-filterswhich may be presented to a sending user based on geographic location.For example, geolocation filters specific to a neighborhood or speciallocation may be presented within a user interface by the messagingclient application 104, based on geolocation information determined by aGlobal Positioning System (GPS) unit of the client device 102. Anothertype of filter is a data filter, which may be selectively presented to asending user by the messaging client application 104, based on otherinputs or information gathered by the client device 102 during themessage creation process. Examples of data filters include currenttemperature at a specific location, a current speed at which a sendinguser is traveling, battery life for a client device 102, or the currenttime.

Other annotation data that may be stored within the image table 308 isso-called “lens” data. A “lens” may be a real-time special effect andsound that may be added to an image or a video.

As mentioned above, the video table 310 stores video data which, in oneembodiment, is associated with messages for which records are maintainedwithin the message table 314. Similarly, the image table 308 storesimage data associated with messages for which message data is stored inthe entity table 302. The entity table 302 may associate variousannotations from the annotation table 312 with various images and videosstored in the image table 308 and the video table 310,

A story table 306 stores data regarding collections of messages andassociated image, video, or audio data, which are compiled into acollection (e.g., a SNAPCHAT story or a gallery). The creation of aparticular collection may be initiated by a particular user (e.g., eachuser for which a record is maintained in the entity table 302). A usermay create a “personal story” in the form of a collection of contentthat has been created and sent/broadcast by that user. To this end, theuser interface of the messaging client application 104 may include anicon that is user selectable to enable a sending user to add specificcontent to his or her personal story.

A collection may also constitute a “live story,” which is a collectionof content from multiple users that is created manually, automatically,or using a combination of manual and automatic techniques. For example,a “live story” may constitute a curated stream of user-submitted contentfrom various locations and events. Users, whose client devices havelocation services enabled and are at a common location event at aparticular time, may, for example, be presented with an option, via auser interface of the messaging client application 104, to contributecontent to a particular live story. The live story may be identified tothe user by the messaging client application 104 based on his or herlocation. The end result is a “live story” told from a communityperspective.

A further type of content collection is known as a “location story,”which enables a user whose client device 102 is located within aspecific geographic location (e.g., on a college or university campus)to contribute to a particular collection. In some embodiments, acontribution to a location story may require a second degree ofauthentication to verify that the end user belongs to a specificorganization or other entity (e.g., is a student on the universitycampus).

The database 120 also stores reference images in the reference imagetable 316. Each reference image includes a captured image (e.g.,photograph) of a real-world feature. Each reference image includesmetadata describing the reference image, such as metadata indicating thereal-world feature captured by the reference image as well ascategorization data describing one or more categories associated withthe reference image. Categorization data includes general categorizationand various level of specific categorization for the reference image.The categorization data also include a contextual categorization of thereference image.

FIG. 4 is a schematic diagram illustrating a structure of a message 400,according to some embodiments, generated by a messaging clientapplication 104 for communication to a further messaging clientapplication 104 or the messaging server application 114. The content ofa particular message 400 is used to populate the message table 314stored within the database 120, which is accessible by the messagingserver application 114. Similarly, the content of a message 400 isstored in memory as “in-transit” or “in-flight” data of the clientdevice 102 or the application server 112. The message 400 is shown toinclude the following components:

-   -   A message identifier 402: a unique identifier that identifies        the message 400.    -   A message text payload 404: text, to be generated by a user via        a user interface of the client device 102 and that is included        in the message 400.    -   A message image payload 406: image data, captured by a camera        component of a client device 102 or retrieved from memory of a        client device 102, and that is included in the message 400.    -   A message video payload 408: video data, captured by a camera        component or retrieved from a memory component of the client        device 102 and that is included in the message 400.    -   A message audio payload 410: audio data, captured by a        microphone or retrieved from the memory component of the client        device 102, and that is included in the message 400.    -   A message annotations 412: annotation data (e.g., filters,        stickers or other enhancements) that represents annotations to        be applied to message image payload 406, message video payload        408, or message audio payload 410 of the message 400.    -   A message duration parameter 414: parameter value indicating, in        seconds, the amount of time for which content of the message        (e.g., the message image payload 406, message video payload 408,        message audio payload 410) is to be presented or made accessible        to a user via the messaging client application 104.    -   A message geolocation parameter 416: geolocation data (e.g.,        latitudinal and longitudinal coordinates) associated with the        content payload of the message. Multiple message geolocation        parameter 416 values may be included in the payload, with each        of these parameter values being associated with respect to        content items included in the content (e.g., a specific image        into within the message image payload 406, or a specific video        in the message video payload 408).    -   A message story identifier 418: identifier values identifying        one or more content collections (e.g., “stories”) with which a        particular content item in the message image payload 406 of the        message 400 is associated. For example, multiple images within        the message image payload 406 may each be associated with        multiple content collections using identifier values.    -   A message tag 420: each message 400 may be tagged with multiple        tags, each of which is indicative of the subject matter of        content included in the message payload. For example, where a        particular image included in the message image payload 406        depicts an animal (e.g., a lion), a tag value may be included        within the message tag 420 that is indicative of the relevant        animal. Tag values may be generated manually, based on user        input, or may be automatically generated using, for example,        image recognition.    -   A message sender identifier 422: an identifier a messaging        system identifier, email address or device identifier)        indicative of a user of the client device 102 on which the        message 400 was generated and from which the message 400 was        sent    -   A message receiver identifier 424: an identifier (e.g., a        messaging system identifier, email address or device identifier)        indicative of a user of the client device 102 to which the        message 400 is addressed.

The contents (e.g. values) of the various components of message 400 maybe pointers to locations in tables within which content data values arestored. For example, an image value in the message image payload 406 maybe a pointer to (or address of) a location within an image table 308.Similarly, values within the message video payload 408 may point to datastored within a video table 310, values stored within the messageannotations 412 may point to data stored in an annotation table 312,values stored within the message story identifier 418 may point to datastored in a story table 306, and values stored within the message senderidentifier 422 and the message receiver identifier 424 may point to userrecords stored within an entity table 302.

FIG. 5 is a schematic diagram illustrating an access-limiting process500, in terms of which access to content (e.g., an ephemeral message502, and associated multimedia payload of data) or a content collection(e.g., an ephemeral message story 504) may be time-limited (e.g., madeephemeral).

An ephemeral message 502 is shown to be associated with a messageduration parameter 506, the value of which determines an amount of timethat the ephemeral message 502 will be displayed to a receiving user ofthe ephemeral message 502 by the messaging client application 104. Inone embodiment, where the messaging client application 104 is a SNAPCHATapplication client, an ephemeral message 502 is viewable by a receivinguser for up to a maximum of 10 seconds, depending on the amount of timethat the sending user specifies using the message duration parameter506.

The message duration parameter 506 and the message receiver identifier424 are shown to be inputs to a message timer 512, which is responsiblefor determining the amount of time that the ephemeral message 502 isshown to a particular receiving user identified by the message receiveridentifier 424. In particular, the ephemeral message 502 will only beshown to the relevant receiving user for a time period determined by thevalue of the message duration parameter 506. The message timer 512 isshown to provide output to a more generalized ephemeral timer system202, which is responsible for the overall timing of display of content(e.g., an ephemeral message 502) to a receiving user.

The ephemeral message 502 is shown in FIG. 5 to be included within anephemeral message story 504 (e.g., a personal SNAPCHAT story, or anevent story). The ephemeral message story 504 has an associated storyduration parameter 508, a value of which determines a time-duration forwhich the ephemeral message story 504 is presented and accessible tousers of the messaging system 100. The story duration parameter 508, forexample, may be the duration of a music concert, where the ephemeralmessage story 504 is a collection of content pertaining to that concert.Alternatively, a user (either the owning user or a curator user) mayspecify the value for the story duration parameter 508 when performingthe setup and creation of the ephemeral message story 504.

Additionally, each ephemeral message 502 within the ephemeral messagestory 504 has an associated story participation parameter 510, a valueof which determines the duration of time for which the ephemeral message502 will be accessible within the context of the ephemeral message story504. Accordingly, a particular ephemeral message story 504 may “expire”and become inaccessible within the context of the ephemeral messagestory 504, prior to the ephemeral message story 504 itself expiring interms of the story duration parameter 508. The story duration parameter508, story participation parameter 510, and message receiver identifier424 each provide input to a story timer 514, which operationallydetermines, firstly, whether a particular ephemeral message 502 of theephemeral message story 504 will be displayed to a particular receivinguser and, if so, for how long. Note that the ephemeral message story 504is also aware of the identity of the particular receiving user as aresult of the message receiver identifier 424.

Accordingly, the story timer 514 operationally controls the overalllifespan of an associated ephemeral message story 504, as well as anindividual ephemeral message 502 included in the ephemeral message story504. In one embodiment, each and every ephemeral message 502. within theephemeral message story 504 remains viewable and accessible for atime-period specified by the story duration parameter 508. In a furtherembodiment, a certain ephemeral message 502 may expire, within thecontext of ephemeral message story 504, based on a story participationparameter 510. Note that a message duration parameter 506 may stilldetermine the duration of time for which a particular ephemeral message502 is displayed to a receiving user, even within the context of theephemeral message story 504. Accordingly, the message duration parameter506 determines the duration of time that a particular ephemeral message502 is displayed to a receiving user, regardless of whether thereceiving user is viewing that ephemeral message 502 inside or outsidethe context of an ephemeral message story 504.

The ephemeral timer system 202 may furthermore operationally remove aparticular ephemeral message 502 from the ephemeral message story 504based on a determination that it has exceeded an associated storyparticipation parameter 510. For example, when a sending user hasestablished a story participation parameter 510 of 24 hours fromposting, the ephemeral timer system 202 will remove the relevantephemeral message 502 from the ephemeral message story 504 after thespecified 24 hours. The ephemeral timer system 202 also operates toremove an ephemeral message story 504 either when the storyparticipation parameter 510 for each and every ephemeral message 502within the ephemeral message story 504 has expired, or when theephemeral message story 504 itself has expired in terms of the storyduration parameter 508.

In certain use cases, a creator of a particular ephemeral message story504 may specify an indefinite story duration parameter 508. In thiscase, the expiration of the story participation parameter 510 for thelast remaining ephemeral message 502 within the ephemeral message story504 will determine when the ephemeral message story 504 itself expires.In this case, a new ephemeral message 502, added to the ephemeralmessage story 504, with a new story participation parameter 510,effectively extends the life of an ephemeral message story 504 to equalthe value of the story participation parameter 510.

Responsive to the ephemeral timer system 202 determining that anephemeral message story 504 has expired (e.g,., is no longeraccessible), the ephemeral timer system 202 communicates with themessaging system 100 (and, for example, specifically the messagingclient application 104) to cause an indicium (e.g., an icon) associatedwith the relevant ephemeral message story 504 to no longer be displayedwithin a user interface of the messaging client application 104.Similarly, when the ephemeral timer system 202 determines that themessage duration parameter 506 for a particular ephemeral message 502has expired, the ephemeral timer system 202 causes the messaging clientapplication 104 to no longer display an indicium (e.g., an icon ortextual identification) associated with the ephemeral message 502.

FIG. 6 is a block diagram 600 illustrating various modules of the imageprocessing system 116, according to certain example embodiments. Theimage processing system 116 is shown as including an image receivingmodule 602, a vector conversion module 604, a distance determinationmodule 606, a subset selection module 608, a feature determinationmodule 610 and a metadata generation module 612. The various modules ofthe image processing system 116 are configured to communicate with eachother (e.g., via a bus, shared memory, or a switch). Any one or more ofthese modules may be implemented using one or more computer processors614 (e.g., by configuring such one or more computer processors toperform functions described for that module) and hence may include oneor more of the computer processors 614.

Any one or more of the modules described may be implemented usinghardware alone (e.g., one or more of the computer processors 614 of amachine (e.g., machine 1500)) or a combination of hardware and software.For example, any described module of the image processing system 116 mayphysically include an arrangement of one or more of the computerprocessors 614 (e.g., a subset of or among the one or more computerprocessors of the machine (e.g., machine 1500)) configured to performthe operations described herein for that module. As another example, anymodule of the image processing system 116 may include software,hardware, or both, that configure an arrangement of one or more computerprocessors 614 (e.g., among the one or more computer processors of themachine (e.g., machine 1500)) to perform the operations described hereinfor that module. Accordingly, different modules of the image processingsystem 116 may include and configure different arrangements of suchcomputer processors 614 or a single arrangement of such computerprocessors 614 at different points in time Moreover, any two or moremodules of the image processing system 116 may be combined into a singlemodule, and the functions described herein for a single module may besubdivided among multiple modules. Furthermore, according to variousexample embodiments, modules described herein as being implementedwithin a single machine, database, or device may be distributed acrossmultiple machines, databases, or devices.

The image receiving module 602 receives images captured by a clientdevice 102. For example, an image is a photograph captured by an opticalsensor (e.g., camera) of the client device 102. An image includes one ormore real-world features, such as physical objects or features thatdescribe a context of the image.

The vector conversion module 604 converts an image into a vector thatrepresents the image. The resulting vector includes a series ofnumerical values that represent elements of the image. For example, thenumerical values may represent an intensity value of each pixel of theimage. Other examples of elements include color components, length,area, circularity, gradient magnitude, gradient direction, or simply thegray-level intensity value, etc. The vector conversion module 604 usesany known algorithm to generate a vector representing an image, althoughthe same algorithm is used to provide vectors that can compared toidentify similar vectors.

The distance determination module 606 determines a distance between atarget vector (e.g., the vector generated for the image received fromthe client device 102) and a set of reference vectors representingreference images. The distance determination module 606 uses any knownalgorithm to determine the distances, such as an algorithm to determinethe Euclidian distance between vectors.

The subset selection module 608 selects a subset of the reference imagesthat are similar to the target image. For example, the subset selectionmodule 608 identifies a subset of target images corresponding toreference vectors that are determined to be closest to the targetvector. This includes either selecting a predetermined number of theclosest target vectors, such as the 5 or 10 vectors that are closest tothe target vector, or selecting the reference images that correspond totarget vectors that are determined to be within a threshold distance ofthe target vector.

The feature determination module 610 determines what real-world featureis included in a target image. The feature determination module 610 usesmetadata associated with the subset of reference images selected by thesubset selection module 608. Each reference image is associated metadatadescribing what real-world feature is included in the target image, aswell as categorization metadata describing one or more categories towhich the depicted real-world image belongs. For example, a referenceimage depicting a shoe may include metadata indicating that the image isof a shoe as well as categorization data describing categories to whichthe shoe belongs, such as clothing, footwear, etc.

The feature determination module 610 uses the metadata associated withthe identified subset of reference images to determine real-worldfeatures included in the target image. For example, if the referenceimages are associated with metadata indicating that the reference imagesdepict a guitar, the feature determination module 610 determines thatthe target image also depicts a guitar.

In some instance, a reference image identified to be similar to thetarget image may in fact be of a real-world feature that is differentthan the real-world feature captured in the target image. To avoidincorrectly identifying real-world features in an image, the featuredetermination module 610 determines whether a threshold number orthreshold percentage of similar reference images provide consistentmetadata to determine the real-world feature included in the targetimage. For example, to determine that a target image is of a shoe, thefeature determination module 610 determines whether at least threereference images determined to be similar to the target image includemetadata indicating that the reference image is of a shoe. As a result,a single incorrectly identified reference image will not cause thefeature determination module 610 to incorrectly identify the real-worldfeature in the target image.

As another example, the feature determination module 610 determineswhether a threshold percentage of the identified reference imagesinclude consistent metadata describing the real-world feature in therespective reference images. For example, the feature determinationmodule 610 determines whether at least 50% of the reference imagesidentified as being similar to the target image include consistentmetadata to cause the feature determination module 610 to determine thatthe target image includes the same real-world feature. Thus, if thefeature determination module 610 identifies ten reference images asbeing similar to a target image, and at least five of the ten referenceimages are identified as being of a guitar, the feature determinationmodule 610 determines that the target image also is of a guitar.

The metadata generation module 612 assigns metadata to a target image.For example, the metadata generation module 612 assigns the metadataassociated with the reference images used to identify the real-worldfeature in the target image to the target image. This includes metadatadescribing the real-world feature depicted in the reference image aswell as categorization metadata for the real-world feature.

FIG. 7 is a block diagram 700 illustrating various modules of anannotation system 206, according to certain example embodiments. Theannotation system 206 is shown as including an image receiving module702, a sensor data receiving module 704, a feature selection module 706,and a media overlay selection module 708. The various modules of theannotation system 206 are configured to communicate with each other(e.g., via a bus, shared memory, or a switch). Any one or more of thesemodules may be implemented using one or more computer processors 710(e.g., by configuring such one or more computer processors to performfunctions described for that module) and hence may include one or moreof the computer processors 710.

Any one or more of the modules described may be implemented usinghardware alone (e.g., one or more of the computer processors 710 of amachine (e.g., machine 1500)) or a combination of hardware and software.For example, any described module of the annotation system 206 mayphysically include an arrangement of one or more of the computerprocessors 710 (e.g., a subset of or among the one or more computerprocessors of the machine (e.g., machine 1500)) configured to performthe operations described herein for that module. As another example, anymodule of the annotation system 206 may include software, hardware, orboth, that configure an arrangement of one or more computer processors710 (e.g., among the one or more computer processors of the machine(e.g., machine 1500)) to perform the operations described herein forthat module. Accordingly, different modules of the annotation system 206may include and configure different arrangements of such computerprocessors 710 or a single arrangement of such computer processors 710at different points in time. Moreover, any two or more modules of theannotation system 206 may be combined into a single module, and thefunctions described herein for a single module may be subdivided amongmultiple modules. Furthermore, according to various example embodiments,modules described herein as being implemented within a single machine,database, or device may be distributed across multiple machines,databases, or devices.

The image receiving module 702 receives images captured by a clientdevice 102. For example, an image is a photograph captured by an opticalsensor (e.g., camera) of the client device 102. An image includes one ormore real-world features, such as physical objects or features thatdescribe a context of the image. In some embodiments, an image includesmetadata describing the image. For example, the image includes metadatadescribing one or more real-world features captured by the image as wellas categorization data describing categories associated with the one ormore real-world features captured by the image. The metadata alsodescribes the appearance of the real-world features within the image.For example, the metadata describes a location of the real-worldfeatures in the image, such as whether the real-world feature ispositioned near the edge of the image or near the center of the image.The metadata also describes the size of each real-world feature inrelation to the image or the other real-world features captured in theimage. For example, the metadata indicates a percentage of the imagethat each real-world feature consumes. As another example, the metadataindicates a ranking of each real-world feature based on its sizecompared to the other real-world features.

The metadata can be added to the image by the image processing system116 prior to the image having been received by the image receivingmodule 702. Alternatively, the image receiving module 702 can providethe image to the image processing system 116 and the image processingsystem identifies the real-world features in the image and addscorresponding metadata to the image. The image processing system 116then provides the image back to the image receiving module.

The sensor data receiving module 704 receives sensor data from a clientdevice 102. Sensor data is any type of data captured by a sensor of theclient device 102. For example, the sensor data includes data describingmotion of the client device 102 gathered by a gyroscope, GPS, or othersensor of the client device 102 that describes a current geographiclocation and/or movement of the client device 102. As another example,sensor data may include temperature data indicating a currenttemperature as detected by a sensor of the client device 102. As anotherexample, the sensor data may include light sensor data indicatingwhether the client device 102 is in a dark or bright environment.

The feature selection module 706 selects one or more real-world featurescaptured by an image to be used as a basis for selecting media overlaysfor the image. For example, in instances where an image includes arelatively high number of real-world features, the feature selectionmodule 706 selects a subset of the real-world features to be used as abasis for selecting media overlays for the image. The feature selectionmodule 706 selects the subset of real-world features based on one ormore factors, such as the size of the real-world features, the locationof the real world features within the image, a distinctiveness orcommonness level of the real-world features, etc. For example, thefeature selection module 706 selects real-world features that arerelatively larger or that take up a larger portion of the image, whichmay indicate that the real-world feature is a focal point of the image.As another example, the feature selection module 706 selects real-worldfeatures located near the center of the image, which may indicate thatthe real-world feature is a focal point of the image. As anotherexample, the feature selection module 706 selects real-world featuresthat are relatively more unique (e.g., distinct) and less commonlycaptured in images. Conversely, the feature selection module 706 mayselect real-world features that are common.

The media overlay selection module 708 uses the real-world featuresselected by the feature selection module 706 to select one or more mediaoverlays for the image. The media overlay selection module 708 uses themetadata describing each real-world feature to identify media overlaysin database 120 for the image. In some embodiments, the media overlayselection module 708 selects media overlays that depict the real-worldfeatures captured in the image. For example, the media overlay selectionmodule 708 selects media overlays depicting a guitar for an image of aguitar.

As another example, the media overlay selection module 708 selects mediaoverlays that are related to the real-world features. For example, themedia overlay selection module 708 determines a category of thereal-world feature, such as a general, specific, or contextual category.The media overlay selection module 708 then select media overlays thatare included in the determined category.

In some embodiments, the media overlay selection module 708 selectsmedia overlays based on the real-world features included in the image aswell as sensor data received from the client device 102. For example,the media overlay selection module 708 uses sensor data such as locationdata, motion data, etc., along with the metadata describing thereal-world features, to determine a category, such as a contextualcategory, describing the image. The media overlay selection module 708then selects media overlays that are included in the determinedcategory.

The media overlay selection module 708 provides the selected mediaoverlays to the client device 102. A user of the client device then usesone or more of the media overlays to annotate the image. For example,the user can use the client device 102 to cause a media overlay to beappended over a user selected portion of the image.

FIG. 8 is a flowchart illustrating a method 800 to select a filtered setof media overlays based on real-world features identified in an image,according to certain example embodiments. The method 800 may be embodiedin computer-readable instructions for execution by one or more computerprocessors such that the operations of the method 800 may be performedin part or in whole by the messaging server system 108; accordingly, themethod 800 is described below by way of example with reference thereto.However, it shall be appreciated that at least some of the operations ofthe method 800 may be deployed on various other hardware configurationsand the method 800 is not intended to be limited to the messaging serversystem 108.

At operation 802, the messaging server system 108 receives, from aclient device 102, image data describing an image captured by an opticalsensor of the client device 102. In addition to the image data, themessaging server system 108 also receives contextual data captured by asensor of the client device 102, such as a location or movement sensor.

At operation 804, the image processing system 116 identifies, based onan analysis of the image data, a first real-world feature captured inthe image. In some embodiments, the first real-world feature is aphysical item captured in the image.

At operation 806, the annotation system 206 selects, based on the firstreal-world feature captured in the image, a first media overlay for usewith the image. The first media overlay is a digital image that can beannotated over the image. In some embodiments, the media overlayselection module 708 identifies a set of one or more media overlays thatdepict the physical item captured in the image. The media overlayselection module 708 selects the first media overlay from the set of oneor more media overlays that depict the physical item captured in theimage.

In some embodiments, the media overlay selection module 708 identifies,based on the physical item captured in the image, a contextual categoryof the image. The media overlay selection module selects the first mediaoverlay from a set of media overlays associated with the contextualcategory.

In some embodiments, the media overlay selection module 708 determines,based on the contextual data captured by the sensor of the client deviceand the first real-world feature, a contextual category of the image.The media overlay selection module 708 selects the first media overlayfrom a set of media overlays associated with the contextual category.

At operation 808, the annotation system 206 transmits the first mediaoverlay to the client device 102. After the first media overlay isreceived by the client device 102, a user of the client device 102 cancause the first media overlay to be appended over a user selectedportion of the image, yielding an annotated image.

FIG. 9 is a flowchart illustrating another method 900 to select afiltered set of media overlays based on real-world features identifiedin an image, according to certain example embodiments. The method 900may be embodied in computer-readable instructions for execution by oneor more computer processors such that the operations of the method 900may be performed in part or in whole by the messaging server system 108;accordingly, the method 900 is described below by way of example withreference thereto. However, it shall be appreciated that at least someof the operations of the method 900 may be deployed on various otherhardware configurations and the method 900 is not intended to be limitedto the messaging server system 108.

At operation 902, the image receiving module 602 receives image datadescribing an image captured by an optical sensor of a client device102. For example, an image is a photograph captured by an optical sensor(e.g., camera) of the client device 102. An image includes one or morereal-world features, such as physical objects or features that describea context of the image.

At operation 904, the image processing system 116 compares the image toa set of references images. The reference images depict known real-worldfeatures. Each reference image includes metadata describing thereal-world image depicted by the respective reference image. In someembodiments, the image processing system 116 uses vectors representingthe images to compare the image to the reference images. For example,the image processing system 116 determines the Euclidian distancebetween the vectors.

At operation 906, the image processing system 116 determines, based onthe comparison, a subset of reference images that are similar to theimage captured by the client device. For example, the image processingsystem 116 determines the subset of reference images that arerepresented by vectors that are closest to the vector representing theimage received from the client device 102.

At operation 908, the image processing system 116 determines, based onassociated. metadata of the subset of images, that the image captured bythe client device 102 depicts a first real-world feature. For example,the image processing system 116 determines what real-world feature ismost commonly depicted by the subset of reference images and determinesthat the image received from the client device 102. depicts the samereal-world feature.

At operation 910, the annotation system 206 selects a subset of mediaoverlays related to the first-real world feature. The annotation system206 uses metadata describing the media overlays to identify mediaoverlays that depict the same real-world image and/or related real-worldfeatures. For example, the annotation system 206 selects media overlaysthat depict real-world features that are included in a same category asthe real-world feature depicted in the image received from the clientdevice 102.

At operation 912, the annotation system transmits the subset of mediaoverlays to the client device 102. A use of the client device 102 canthen select to annotate the image with one or more of the received mediaoverlays.

FIG. 10 is a flowchart illustrating a method 1000 to determine a subsetof reference images that are similar to a target image, according tocertain example embodiments. The method 1000 may be embodied incomputer-readable instructions for execution by one or more computerprocessors such that the operations of the method 1000 may be performedin part or in whole by the messaging server system 108; accordingly, themethod 1000 is described below by way of example with reference thereto.However, it shall be appreciated that at least some of the operations ofthe method 1000 may be deployed on various other hardware configurationsand the method 1000 is not intended to be limited to the messagingserver system 108.

At operation 1002, the image receiving module 602 receives image datadescribing an image captured by an optical sensor of a client device102. For example, an image is a photograph captured by an optical sensor(e.g., camera) of the client device 102. An image includes one or morereal-world features, such as physical objects or features that describea context of the image.

At operation 1004, the vector conversion module 604 generates a targetvector representing the image. The resulting vector includes a series ofnumerical values that represent elements of the image. For example, thenumerical values may represent an intensity value of each pixel of theimage. Other examples of elements include color components, length,area, circularity, gradient magnitude, gradient direction, or simply thegray-level intensity value, etc. The vector conversion module 604 usesany known algorithm to generate a vector representing an image, althoughthe same algorithm is used to provide vectors that can compared toidentify similar vectors.

At operation 1006, the distance determination module 606 determines,using a distance function, a distance between the target vector and aset of reference vectors. The distance determination module 606 uses anyknown algorithm to determine the distances, such as an algorithm todetermine the Euclidian distance between vectors.

At operation 1008, the subset selection module 608 determines, based onthe distance determination, a subset of reference vectors that areclosest to the target vector. For example, the subset selection module608 identifies a subset of target images corresponding to referencevectors that are determined to be closest to the target vector. Thisincludes either selecting a predetermined number of the closest targetvectors, such as the 5 or 10 vectors that are closest to the targetvector, or selecting the reference images that correspond to targetvectors that are determined to be within a threshold distance of thetarget vector.

FIG. 11 is a flowchart illustrating a method 1100 to determine thereal-world feature captured in an image, according to certain exampleembodiments. The method 1100 may be embodied in computer-readableinstructions for execution by one or more computer processors such thatthe operations of the method 1100 may be performed in part or in wholeby the messaging server system 108; accordingly, the method 1100 isdescribed below by way of example with reference thereto. However, itshall be appreciated that at least some of the operations of the method1100 may be deployed on various other hardware configurations and themethod 1100 is not intended to be limited to the messaging server system108.

At operation 1102, the feature determination module 608 determines apercentage of the reference images that are associated with metadataindicating that the respective reference images depict the samereal-world feature. The reference images are selected by the imageprocessing system 116 based on a target image. The feature determinationmodule 608 uses metadata associated with the reference images todetermine what real-world feature is depicted in the reference imagesand determines the largest set of reference images that depict the samereal-world image. The feature determination module 608 then determineswhat percentage of the reference images selected based on the targetimage depict the same real-world feature.

At operation 1104, the media overlay selection module 708 compares thepercentage to a threshold percentage. The threshold percentage is apredetermined threshold used to determine if the reference images depictthe same real-world feature as the image.

At operation 1106, the media overlay selection module 708 determinesthat the percentage meets or exceeds the threshold percentage. Thisindicates that the real-world feature in the image is the same as thereal-world feature depicted in the reference images.

FIG. 12 is a flowchart illustrating a method 1200 to select a mediaoverlay, according to certain example embodiments. The method 1200 maybe embodied in computer-readable instructions for execution by one ormore computer processors such that the operations of the method 1200 maybe performed in part or in whole by the messaging server system 108;accordingly, the method 1200 is described below by way of example withreference thereto. However, it shall be appreciated that at least someof the operations of the method 1200 may be deployed on various otherhardware configurations and the method 1200 is not intended to belimited to the messaging server system 108.

At operation 1202, the media overlay selection module 708 determines amedia overlay that depicts the real-world feature depicted in an imagereceived from the client device 102. For example, the media overlayselection module uses metadata associated with the image to determinewhat real-world feature is depicted in the image. The media overlayselection module 708 then uses metadata associated with the mediaoverlays to identify a media overlay that depicts the same real-worldimage.

At operation 1204, the media overlay selection module 708 determines asize of the real-world feature as depicted in the image received fromthe client device. The size of the image as depicted in the imageindicates a size at which the real-world feature will presented whendisplayed by a client device 102. The image processing system 116determines the size of the real-world feature as depicted in the imageand associates metadata with the image identifying the size. The mediaoverlay selection module 708 uses the metadata to determine the size ofthe real-world feature.

At operation 1206, the media overlay selection module 708 adjusts thesize of the media overlay based on the size of the real-world feature asdepicted in the image received from the client device. For example, themedia overlay selection module 708 adjusts the size so that the mediaoverlay is presented at the same or similar size as the real-world imageon the display of the client device 102. A user can place the mediaoverlay over the real-world feature in the image to annotate the image.For example, the user can place a media overlay depicting a soda canover a soda can captured in the image,

FIG. 13 is a flowchart illustrating another method 1300 to select amedia overlay, according to certain example embodiments. The method 1300may be embodied in computer-readable instructions for execution by oneor more computer processors such that the operations of the method 1300may be performed in part or in whole by the messaging server system 108;accordingly, the method 1300 is described below by way of example withreference thereto. However, it shall be appreciated that at least someof the operations of the method 1300 may be deployed on various otherhardware configurations and the method 1300 is not intended to belimited to the messaging server system 108.

At operation 1302, the media overlay selection module 708 determines acategory associated with the real-world object captured in an imagereceived from the client device 102. The real-world object is associatedwith metadata describing the real-world object captured in the image.The metadata is associated with the image by the image processing system116. The metadata includes categorization metadata describing one ormore categories to which the real-world feature belongs. The mediaoverlay selection module 708 uses the metadata to determine the categoryassociated with the real-world object.

At operation 1304, the media overlay selection module 708 determines aset of media overlays based on the category associated with thereal-world object captured in the image received from the client device102. Available media overlays are associated with metadata describingeach respective media overlay. For example, the media overlays areassociated with metadata describing an image depicted by the mediaoverlay, as well as categorization data describing a category to whichthe media overlay belongs. For example, a media overlay depicting a shoeis associated with metadata indicating that the media overlay depicts ashoe, as well as categorization data for the shoe, such as clothing,footwear, Nike, etc.

The media overlay selection module 708 uses the metadata to identify asubset of media overlays that are included in the same category as theimage. For example, if the image is of a shoe, the media overlayselection module 708 identifies media overlays that are categorized asfootwear.

At operation 1306, the media overlay selection module 708 selects atleast one media overlay from the set of media overlays. The mediaoverlay selection module 708 selects the media overlays based on anynumber of factors. For example, the media overlay selection module 708selects media overlays based on popularity (e.g., how often they areused to annotate an image), how similar the media overlay is to theimage (e.g., a media overlay that depicts the real-world feature), etc.

Software Architecture

FIG. 14 is a block diagram illustrating an example software architecture1406, which may be used in conjunction with various hardwarearchitectures herein described. FIG. 14 is a non-limiting example of asoftware architecture and it will be appreciated that many otherarchitectures may be implemented to facilitate the functionalitydescribed herein. The software architecture 1406 may execute on hardwaresuch as machine 1500 of FIG. 15 that includes, among other things,processors 1504, memory 1514, and (input/output) I/O components 1518. Arepresentative hardware layer 1452 is illustrated and can represent, forexample, the machine 1500 of FIG. 15. The representative hardware layer1452 includes a processing unit 1454 having associated executableinstructions 1404. Executable instructions 1404 represent the executableinstructions of the software architecture 1406, including implementationof the methods, components, and so forth described herein. The hardwarelayer 1452 also includes memory and/or storage modules memory/storage1456, which also have executable instructions 1404. The hardware layer1452 may also comprise other hardware 1458.

In the example architecture of FIG. 14, the software architecture 1406may be conceptualized as a stack of layers where each layer providesparticular functionality. For example, the software architecture 1406may include layers such as an operating system 1402, libraries 1420,frameworks/middleware 1418, applications 1416, and a presentation layer1414. Operationally, the applications 1416 and/or other componentswithin the layers may invoke API calls 1408 through the software stackand receive a response as in response to the API calls 1408. The layersillustrated are representative in nature and not all softwarearchitectures have all layers. For example, some mobile or specialpurpose operating systems may not provide a frameworks/middleware 1418,while others may provide such a layer. Other software architectures mayinclude additional or different layers.

The operating system 1402 may manage hardware resources and providecommon services. The operating system 1402 may include, for example, akernel 1422, services 1424, and drivers 1426. The kernel 1422 may act asan abstraction layer between the hardware and the other software layers.For example, the kernel 1422 may be responsible for memory management,processor management (e.g., scheduling), component management,networking, security settings, and so on. The services 1424 may provideother common services for the other software layers. The drivers 1426are responsible for controlling or interfacing with the underlyinghardware. For instance, the drivers 1426 include display drivers, cameradrivers, Bluetooth® drivers, flash memory drivers, serial communicationdrivers (e.g., Universal Serial Bus (USB) drivers Wi-Fi® drivers, audiodrivers, power management drivers, and so forth depending on thehardware configuration.

The libraries 1420 provide a common infrastructure that is used by theapplications 1416 and/or other components and/or layers. The libraries1420 provide functionality that allows other software components toperform tasks in an easier fashion than to interface directly with theunderlying operating system 1402 functionality (e.g., kernel 1422,services 1424 and/or drivers 1426). The libraries 1420 may includesystem libraries 1444 (e.g., C standard library) that may providefunctions such as memory allocation functions, string manipulationfunctions, mathematical functions, and the like. In addition, thelibraries 1420 may include API libraries 1446 such as media libraries(e.g., libraries to support presentation and manipulation of variousmedia format such as MPREG4, H.264, MP3, AAC, AMR, JPG, PNG), graphicslibraries (e.g., an OpenGL framework that may be used to render 2D and3D in a graphic content on a display), database libraries (e.g., SQLitethat may provide various relational database functions), web libraries(e.g., WebKit that may provide web browsing functionality), and thelike. The libraries 1420 may also include a wide variety of otherlibraries 1448 to provide many other APIs to the applications 1416 andother software components/modules.

The frameworks/middleware 1418 (also sometimes referred to asmiddleware) provide a higher-level common infrastructure that may beused by the applications 1416 and/or other software components/modules.For example, the frameworks/middleware 1418 may provide various graphicuser interface (GUI) functions, high-level resource management,high-level location services, and so forth. The frameworks/middleware1418 may provide a broad spectrum of other APIs that may be used by theapplications 1416 and/or other software components/modules, some ofwhich may be specific to a particular operating system 1402 or platform.

The applications 1416 include built-in applications 1438 and/orthird-party applications 1440. Examples of representative built-inapplications 1438 may include, but are not limited to, a contactsapplication, a browser application, a book reader application, alocation application, a media application, a messaging application,and/or a game application. Third-party applications 1440 may include anapplication developed using the ANDROID™ or IOS™ software developmentkit (SDK) by an entity other than the vendor of the particular platform,and may be mobile software running on a mobile operating system such asIOS™ ANDROID™, WINDOWS® Phone, or other mobile operating systems. Thethird-party applications 1440 may invoke the API calls 1408 provided bythe mobile operating system (such as operating system 1402) tofacilitate functionality described herein.

The applications 1416 may use built in operating system functions (e.g.,kernel 1422, services 1424 and/or drivers 1426), libraries 1420, andframeworks/middleware 1418 to create user interfaces to interact withusers of the system. Alternatively, or additionally, in some systemsinteractions with a user may occur through a presentation layer, such aspresentation layer 1414. In these systems, the application/component“logic” can be separated from the aspects of the application/componentthat interact with a user.

FIG. 15 is a block diagram illustrating components of a machine 1500,according to some example embodiments, able to read instructions from amachine-readable medium (e.g., a machine-readable storage medium) andperform any one or more of the methodologies discussed herein.Specifically, FIG. 15 shows a diagrammatic representation of the machine1500 in the example form of a computer system, within which instructions1510 (e.g., software, a program, an application, an applet, an app, orother executable code) for causing the machine 1500 to perform any oneor more of the methodologies discussed herein may be executed. As such,the instructions 1510 may be used to implement modules or componentsdescribed herein. The instructions 1510 transform the general,non-programmed machine 1500 into a particular machine 1500 programmed tocarry out the described and illustrated functions in the mannerdescribed. In alternative embodiments, the machine 1500 operates as astandalone device or may be coupled (e.g., networked) to other machines.In a networked deployment, the machine 1500 may operate in the capacityof a server machine or a client machine in a server-client networkenvironment, or as a peer machine in a peer-to-peer (or distributed)network environment. The machine 1500 may comprise, but not be limitedto, a server computer, a client computer, a personal computer (PC), atablet computer, a laptop computer, a netbook, a set-top box (STB), apersonal digital assistant (PDA), an entertainment media system, acellular telephone, a smart phone, a mobile device, a wearable device(e.g., a smart watch), a smart home device (e.g., a smart appliance),other smart devices, a web appliance, a network router, a networkswitch, a network bridge, or any machine capable of executing theinstructions 1510, sequentially or otherwise, that specify actions to betaken by machine 1500. Further, while only a single machine 1500 isillustrated, the term “machine” shall also be taken to include acollection of machines that individually or jointly execute theinstructions 1510 to perform any one or more of the methodologiesdiscussed herein.

The machine 1500 may include processors 1504, memory memory/storage1506, and I/O components 1518, which may be configured to communicatewith each other such as via a bus 1502. The memory/storage 1506 mayinclude a memory 1514, such as a main memory, or other memory storage,and a storage unit 1516, both accessible to the processors 1504 such asvia the bus 1502. The storage unit 1516 and memory 1514 store theinstructions 1510 embodying any one or more of the methodologies orfunctions described herein. The instructions 1510 may also reside,completely or partially, within the memory 1514, within the storage unit1516, within at least one of the processors 1504 (e.g., within theprocessor's cache memory), or any suitable combination thereof, duringexecution thereof by the machine 1500. Accordingly, the memory 1514, thestorage unit 1516, and the memory of processors 1504 are examples ofmachine-readable media.

The I/O components 1518 may include a wide variety of components toreceive input, provide output, produce output, transmit information,exchange information, capture measurements, and so on. The specific I/Ocomponents 1518 that are included in a particular machine 1500 willdepend on the type of machine. For example, portable machines such asmobile phones will likely include a touch input device or other suchinput mechanisms, while a headless server machine will likely notinclude such a touch input device. It will be appreciated that the I/Ocomponents 1518 may include many other components that are not shown inFIG. 15. The I/O components 1518 are grouped according to functionalitymerely for simplifying the following discussion and the grouping is inno way limiting. In various example embodiments, the I/O components 1518may include output components 1526 and input components 1528. The outputcomponents 1526 may include visual components (e.g., a display such as aplasma display panel (PDP), a light emitting diode (LED) display, aliquid crystal display (LCD), a projector, or a cathode ray tube (CRT)),acoustic components (e.g., speakers), haptic components (e.g., avibratory motor, resistance mechanisms), other signal generators, and soforth. The input components 1528 may include alphanumeric inputcomponents (e.g., a keyboard, a touch screen configured to receivealphanumeric input, a photo-optical keyboard, or other alphanumericinput components), point based input components (e.g., a mouse, atouchpad, a trackball, a joystick, a motion sensor, or other pointinginstrument), tactile input components (e.g., a physical button, a touchscreen that provides location and/or force of touches or touch gestures,or other tactile input components), audio input components (e.g., amicrophone), and the like.

In further example embodiments, the I/O components 1518 may includebiometric components 1530, motion components 1534, environmentalcomponents 1536, or position components 1538 among a wide array of othercomponents. For example, the biometric components 1530 may includecomponents to detect expressions (e.g., hand expressions, facialexpressions, vocal expressions, body gestures, or eye tracking), measurebiosignals (e.g., blood pressure, heart rate, body temperature,perspiration, or brain waves), identify a person (e.g., voiceidentification, retinal identification, facial identification,fingerprint identification, or electroencephalogram basedidentification), and the like. The motion components 1534 may includeacceleration sensor components (e.g., accelerometer), gravitation sensorcomponents, rotation sensor components (e.g., gyroscope), and so forth.The environment components 1536 may include, for example, illuminationsensor components (e.g., photometer), temperature sensor components(e.g., one or more thermometer that detect ambient temperature),humidity sensor components, pressure sensor components (e.g.,barometer), acoustic sensor components (e.g., one or more microphonesthat detect background noise), proximity sensor components (e.g.,infrared sensors that detect nearby objects), gas sensors (e.g., gasdetection sensors to detection concentrations of hazardous gases forsafety or to measure pollutants in the atmosphere), or other componentsthat may provide indications, measurements, or signals corresponding toa surrounding physical environment. The position components 1538 mayinclude location sensor components (e.g., a GPS receiver component),altitude sensor components (e.g., altimeters or barometers that detectair pressure from which altitude may be derived), orientation sensorcomponents (e.g., magnetometers), and the like.

Communication may be implemented using a wide variety of technologies.The I/O components 1518 may include communication components 1540operable to couple the machine 1500 to a network 1532 or devices 1520via coupling 1524 and coupling 1522, respectively. For example, thecommunication components 1540 may include a network interface componentor other suitable device to interface with the network 1532. In furtherexamples, communication components 1540 may include wired communicationcomponents, wireless communication components, cellular communicationcomponents, Near Field Communication (NFC) components, Bluetooth®components (e.g., Bluetooth® Low Energy), Wi-Fi® components, and othercommunication components to provide communication via other modalities.The devices 1520 may be another machine or any of a wide variety ofperipheral devices (e.g., a peripheral device coupled via a USB).

Moreover, the communication components 1540 may detect identifiers orinclude components operable to detect identifiers. For example, thecommunication components 1540 may include Radio Frequency Identification(RID) tag reader components, NFC smart tag detection components, opticalreader components (e.g., an optical sensor to detect one-dimensional barcodes such as Universal Product Code (UPC) bar code, multi-dimensionalbar codes such as Quick Response (QR) code, Aztec code, Data Matrix,Dataglyph, MaxiCode, PDF417, Ultra Code, UCC RSS-2D bar code, and otheroptical codes), or acoustic detection components (e.g., microphones toidentify tagged audio signals). In addition, a variety of informationmay be derived via the communication components 1540, such as, locationvia Internet Protocol (IP) geo-location, location via Wi-Fi® signaltriangulation, location via detecting a NIT beacon signal that mayindicate a particular location, and so forth.

Glossary

“CARRIER SIGNAL” in this context refers to any intangible medium that iscapable of storing, encoding, or carrying instructions for execution bythe machine, and includes digital or analog communications signals orother intangible medium to facilitate communication of suchinstructions. Instructions may be transmitted or received over thenetwork using a transmission medium via a network interface device andusing any one of a number of well-known transfer protocols.

“CLIENT DEVICE” in this context refers to any machine that interfaces toa communications network to obtain resources from one or more serversystems or other client devices. A client device may be, but is notlimited to, a mobile phone, desktop computer, laptop, PDAs, smartphones, tablets, ultra books, netbooks, laptops, multi-processorsystems, microprocessor-based or programmable consumer electronics, gameconsoles, STBs, or any other communication device that a user may use toaccess a network.

“COMMUNICATIONS NETWORK” in this context refers to one or more portionsof a network that may be an ad hoc network, an intranet, an extranet, avirtual private network (VPN), a local area network (LAN), a wirelessLAN (WLAN), a wide area network (WAN), a wireless WAN (WWAN), ametropolitan area network (MAN), the Internet, a portion of theInternet, a portion of the Public Switched Telephone Network (PSTN), aplain old telephone service (POTS) network, a cellular telephonenetwork, a wireless network, a network, another type of network, or acombination of two or more such networks. For example, a network or aportion of a network may include a wireless or cellular network and thecoupling may be a Code Division Multiple Access (CDMA) connection, aGlobal System for Mobile communications (GSM) connection, or other typeof cellular or wireless coupling. In this example, the coupling mayimplement any of a variety of types of data transfer technology, such asSingle Carrier Radio Transmission Technology (1×RTT), Evolution-DataOptimized (EVDO) technology, General Packet Radio Service (GPRS)technology, Enhanced Data rates for GSM Evolution (EDGE) technology,third Generation Partnership Project (3GPP) including 3G, fourthgeneration wireless (4G) networks, Universal Mobile TelecommunicationsSystem (UMTS), High Speed Packet Access (HSPA), WorldwideInteroperability for Microwave Access (WiMAX), Long Term Evolution (LTE)standard, others defined by various standard setting organizations,other long range protocols, or other data transfer technology.

“EMPHEMERAL MESSAGE” in this context refers to a message that isaccessible for a time-limited duration. An ephemeral message may be atext, an image, a video, and the like. The access time for the ephemeralmessage may be set by the message sender. Alternatively, the access timemay be a default setting or a setting specified by the recipient.Regardless of the setting technique, the message is transitory.

“MACHINE-READABLE MEDIUM” in this context refers to a component, deviceor other tangible media able to store instructions and data temporarilyor permanently and may include, but is not be limited to, random-accessmemory (RAM), read-only memory (ROM), buffer memory, flash memory,optical media, magnetic media, cache memory, other types of storage(e.g., Erasable Programmable Read-Only Memory (EEPROM)), and/or anysuitable combination thereof. The term “machine-readable medium” shouldbe taken to include a single medium or multiple media (e.g., acentralized or distributed database, or associated caches and servers)able to store instructions. The term “machine-readable medium” shallalso be taken to include any medium, or combination of multiple media,that is capable of storing instructions (e.g., code) for execution by amachine, such that the instructions, when executed by one or moreprocessors of the machine, cause the machine to perform any one or moreof the methodologies described herein. Accordingly, a “machine-readablemedium” refers to a single storage apparatus or device, as well as“cloud-based” storage systems or storage networks that include multiplestorage apparatus or devices. The term “machine-readable medium”excludes signals per se.

“COMPONENT” in this context refers to a device, physical entity, orlogic having boundaries defined by function or subroutine calls, branchpoints, APIs, or other technologies that provide for the partitioning ormodularization of particular processing or control functions. Componentsmay be combined via their interfaces with other components to carry outa machine process. A component may be a packaged functional hardwareunit designed for use with other components and a part of a program thatusually performs a particular function of related functions. Componentsmay constitute either software components (e.g., code embodied on amachine-readable medium) or hardware components. A “hardware component”is a tangible unit capable of performing certain operations and may beconfigured or arranged in a certain physical manner. In various exampleembodiments, one or more computer systems (e.g., a standalone computersystem, a client computer system, or a server computer system) or one ormore hardware components of a computer system (e.g., a processor or agroup of processors) may be configured by software (e.g., an applicationor application portion) as a hardware component that operates to performcertain operations as described herein. A hardware component may also beimplemented mechanically, electronically, or any suitable combinationthereof. For example, a hardware component may include dedicatedcircuitry or logic that is permanently configured to perform certainoperations. A hardware component may be a special-purpose processor,such as a Field-Programmable Gate Array (FPGA) or an ApplicationSpecific Integrated Circuit (ASIC). A hardware component may alsoinclude programmable logic or circuitry that is temporarily configuredby software to perform certain operations. For example, a hardwarecomponent may include software executed by a general-purpose processoror other programmable processor. Once configured by such software,hardware components become specific machines (or specific components ofa machine) uniquely tailored to perform the configured functions and areno longer general-purpose processors. It will be appreciated that thedecision to implement a hardware component mechanically, in dedicatedand permanently configured circuitry, or in temporarily configuredcircuitry (e.g., configured by software), may be driven by cost and timeconsiderations. Accordingly, the phrase “hardware component” (or“hardware-implemented component”) should be understood to encompass atangible entity, be that an entity that is physically constructed,permanently configured (e.g., hardwired), or temporarily configured(e.g., programmed) to operate in a certain manner or to perform certainoperations described herein. Considering embodiments in which hardwarecomponents are temporarily configured (e.g., programmed), each of thehardware components need not be configured or instantiated at any oneinstance in time. For example, where a hardware component comprises ageneral-purpose processor configured by software to become aspecial-purpose processor, the general-purpose processor may beconfigured as respectively different special-purpose processors (e.g.,comprising different hardware components) at different times. Softwareaccordingly configures a particular processor or processors, forexample, to constitute a particular hardware component at one instanceof time and to constitute a different hardware component at a differentinstance of time. Hardware components can provide information to, andreceive information from, other hardware components. Accordingly, thedescribed hardware components may be regarded as being communicativelycoupled. Where multiple hardware components exist contemporaneously,communications may be achieved through signal transmission (e.g., overappropriate circuits and buses) between or among two or more of thehardware components. In embodiments in which multiple hardwarecomponents are configured or instantiated at different times,communications between such hardware components may be achieved, forexample, through the storage and retrieval of information in memorystructures to which the multiple hardware components have access. Forexample, one hardware component may perform an operation and store theoutput of that operation in a memory device to which it iscommunicatively coupled. A further hardware component may then, at alater time, access the memory device to retrieve and process the storedoutput. Hardware components may also initiate communications with inputor output devices, and can operate on a resource (e.g., a collection ofinformation). The various operations of example methods described hereinmay be performed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implementedcomponents that operate to perform one or more operations or functionsdescribed herein. As used herein, “processor-implemented component”refers to a hardware component implemented using one or more processors.Similarly, the methods described herein may be at least partiallyprocessor-implemented, with a particular processor or processors beingan example of hardware. For example, at least some of the operations ofa method may be performed by one or more processors orprocessor-implemented components. Moreover, the one or more processorsmay also operate to support performance of the relevant operations in a“cloud computing” environment or as a “software as a service” (SaaS).For example, at least some of the operations may be performed by a groupof computers (as examples of machines including processors), with theseoperations being accessible via a network (e.g., the Internet) and viaone or more appropriate interfaces (e.g., an API). The performance ofcertain of the operations may be distributed among the processors, notonly residing within a single machine, but deployed across a number ofmachines. In sonic example embodiments, the processors orprocessor-implemented components may be located in a single geographiclocation (e.g., within a home environment, an office environment, or aserver farm). In other example embodiments, the processors orprocessor-implemented components may be distributed across a number ofgeographic locations.

“PROCESSOR” in this context refers to any circuit or virtual circuit (aphysical circuit emulated by logic executing on an actual processor)that manipulates data values according to control signals (e.g.,“commands,” “op codes,” “machine code,” etc,) and which producescorresponding output signals that are applied to operate a machine. Aprocessor may be, for example, a Central Processing Unit (CPU), aReduced Instruction Set Computing (RISC) processor, a ComplexInstruction Set Computing (CISC) processor, a Graphics Processing Unit(GPU), a Digital Signal Processor (DSP), an ASIC, a Radio-FrequencyIntegrated Circuit (RFIC) or any combination thereof. A processor mayfurther be a multi-core processor having two or more independentprocessors (sometimes referred to as “cores”) that may executeinstructions contemporaneously.

“TIMESTAMP” in this context refers to a sequence of characters orencoded information identifying when a certain event occurred, forexample giving date and time of day, sometimes accurate to a smallfraction of a second.

Description

A portion of the disclosure of this patent document contains materialthat is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure, as it appears in the Patent and TrademarkOffice patent files or records, but otherwise reserves all copyrightrights whatsoever. The following notice applies to the software and dataas described below and in the drawings that form a part of thisdocument: Copyright 2017, SNAP INC., All Rights Reserved.

What is claimed is:
 1. A method comprising: receiving, from a clientdevice, image data determining an image captured by an optical sensor ofthe client device; determining that the image captured by the opticalsensor of the client device depicts a first real-world feature;determining, based on metadata associated with a plurality of mediaoverlays that describes a respective media overlay, a collection ofmedia overlays that depict real-world features that are associated witha contextual category of the image; selecting a media overlay from thecollection of media overlays based on popularity, wherein the popularityindicates how often each of the media overlays in the collection areused to annotate a respective image; and generating instructions todisplay of the selected media overlay on the client device.
 2. Themethod of claim 1, further comprising: receiving, from the clientdevice, motion data representing movement of the client device; andautomatically selecting the media overlay from the collection mediaoverlays related to the first real-world feature based on the motiondata representing movement of the client device.
 3. The method of claim1, wherein the media overlay is a graphic that augments the imagecaptured by the optical sensor of the client device.
 4. The method ofclaim 1, further comprising: comparing, based on the image data, theimage captured by the client device to a set of reference images,yielding a comparison, each reference image from the set of referenceimages including associated metadata describing a real-world featuredepicted by the respective reference image; determining, based on thecomparison, a subset of reference images that within a defined degree ofsimilarity to the image captured by the optical sensor of the clientdevice; selecting, from a set of media overlays, a subset of mediaoverlays related to the first real-world feature; and transmitting thesubset of media overlays to the client device.
 5. The method of claim 1,further comprising: generating, based on the image data, a target vectorrepresenting the image captured by the client device, the target vectorincluding numeric values describing features of the image; anddetermining, using a distance function, a distance between the targetvector and a set of reference vectors, yielding a distancedetermination, each reference vector from the set of reference vectorsrepresenting a respective reference image from a set of reference imagesand including numeric values describing features of the respectivereference image, wherein the collection of media overlays are determinedbased on the distance between the target vector and the set of referencevectors.
 6. The method of claim 1, further comprising: determining,based on a distance determination, a subset of reference vectors thatare closest to a target vector, the subset of reference vectorsrepresenting a subset of reference images that are similar to the imagecaptured by the optical sensor of the client device, wherein thecollection of media overlays are determined based on the distancedetermination.
 7. The method of claim 1, further comprising:determining, based on associated metadata of a subset of referenceimages, a percentage of the subset of reference images associated withmetadata indicating that the respective reference image depicts an imageof the first real-world feature; comparing the percentage to a thresholdpercentage; and in response to determining the percentage meets orexceeds the threshold percentage, determining that the image depicts thefirst real-world feature.
 8. The method of claim 1, further comprising:determining, based on associated metadata of a subset of referenceimages, a number that represents how many of the subset of referenceimages is associated with metadata indicating that the respectivereference image depicts an image of the first real-world feature;comparing the number to a threshold; in response to determining thenumber transgresses the threshold, determining that the image depictsthe first real-world feature.
 9. The method of claim 1, furthercomprising: determining a size of the first real-world feature asdepicted in the first image; and adjusting a size of the media overlaybased on the size of the first real-world feature as depicted in thefirst image.
 10. The method of claim 1, further comprising: determining,based on the first real-world feature and contextual data received fromthe client device, a contextual category of the image.
 11. A systemcomprising: one or more computer processors; and one or morecomputer-readable mediums storing instructions that, when executed bythe one or more computer processors, cause the system to performoperations comprising: receiving, from a client device, image datadefining an image captured by an optical sensor of the client device;determining that the image captured by the optical sensor of the clientdevice depicts a first real-world feature; determining, based onmetadata associated with a plurality of media overlays that describes arespective media overlay, a collection of media overlays that depictreal-world features that are associated with a contextual category ofthe image; selecting a media overlay from the collection of mediaoverlays based on popularity, wherein the popularity indicates how ofteneach of the media overlays in the collection are used to annotate arespective image; and generating instructions to display of the selectedmedia overlay on the client device.
 17. The system of claim 11, whereinthe operations further comprise: receiving, from the client device,motion data representing movement of the client device; andautomatically selecting the media overlay from the collection mediaoverlays related to the first real-world feature based on the motiondata representing movement of the client device.
 13. The system of claim11, wherein the media overlay is a graphic that augments the imagecaptured by the optical sensor of the client device.
 14. The system ofclaim 11, wherein the operations further comprise: comparing, based onthe image data, the image captured by the client device to a set ofreference images, yielding a comparison, each reference image from theset of reference images including associated metadata describing areal-world feature depicted by the respective reference image;determining, based on the comparison, a subset of reference images thatwithin a defined degree of similarity to the image captured by theoptical sensor of the client device; selecting, from a set of mediaoverlays, a subset of media overlays related to the first real-worldfeature; and transmitting the subset of media overlays to the clientdevice.
 15. The system of claim 11, wherein the operations furthercomprise: generating, based on the image data, a target vectorrepresenting the image captured by the client device, the target vectorincluding numeric values describing features of the image; anddetermining, using a distance function, a distance between the targetvector and a set of reference vectors, yielding a distancedetermination, each reference vector from the set of reference vectorsrepresenting a respective reference image from a set of reference imagesand including numeric values describing features of the respectivereference image, wherein the collection of media overlays are determinedbased on the distance between the target vector and the set of referencevectors.
 16. The system of claim 11, wherein the operations furthercomprise: determining, based on a distance determination, a subset ofreference vectors that are closest to a target vector, the subset ofreference vectors representing a subset of reference images that aresimilar to the image captured by the optical sensor of the clientdevice, wherein the collection of media overlays are determined based onthe distance determination.
 17. The system of claim 11, wherein theoperations further comprise: determining, based on associated metadataof a subset of reference images, a percentage of the subset of referenceimages associated with metadata indicating that the respective referenceimage depicts an image of the first real-world feature; comparing thepercentage to a threshold percentage; and in response to determining thepercentage meets or exceeds the threshold percentage, determining thatthe image depicts the first real-world feature.
 18. The system of claim11, wherein the operations further comprise: determining, based onassociated metadata of a subset of reference images, a number thatrepresents how many of the subset of reference images is associated withmetadata indicating that the respective reference image depicts an imageof the first real-world feature; comparing the number to a threshold; inresponse to determining the number transgresses the threshold,determining that the image depicts the first real-world feature.
 19. Thesystem of claim 11, wherein the operations further comprise: determininga size of the first real-world feature as depicted in the first image;and adjusting a size of the media overlay based on the size of the firstreal-world feature as depicted in the first image.
 20. A non-transitorycomputer-readable medium storing instructions that, when executed by oneor more computer processors of a computing device, cause the computingdevice to perform operations comprising: receiving, from a clientdevice, image data defining an image captured by an optical sensor ofthe client device; determining that the image captured by the opticalsensor of the client device depicts a first real-world feature;determining, based on metadata associated with a plurality of mediaoverlays that describes a respective media overlay, a collection ofmedia overlays that depict real-world features that are associated witha contextual category of the image; selecting a media overlay from thecollection of media overlays based on popularity, wherein the popularityindicates how often each of the media overlays in the collection areused to annotate a respective image; and generating instructions todisplay of the selected media overlay on the client device.